An Approximate Dynamic Programming Approach to Network Revenue Management with Customer Choice Journal Article uri icon



  • We consider a network revenue management problem where customers choose among open fare products according to some prespecified choice model. Starting with a Markov decision process (MDP) formulation, we approximate the value function with an affine function of the state vector. We show that the resulting problem provides a tighter bound for the MDP value than the choice-based linear program. We develop a column generation algorithm to solve the problem for a multinomial logit choice model with disjoint consideration sets (MNLD). We also derive a bound as a by-product of a decomposition heuristic. Our numerical study shows the policies from our solution approach can significantly outperform heuristics from the choice-based linear program.

publication date

  • August 1, 2009

has restriction

  • closed

Date in CU Experts

  • June 26, 2014 10:00 AM

Full Author List

  • Zhang D; Adelman D

author count

  • 2

Other Profiles

International Standard Serial Number (ISSN)

  • 0041-1655

Electronic International Standard Serial Number (EISSN)

  • 1526-5447

Additional Document Info

start page

  • 381

end page

  • 394


  • 43


  • 3